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Data from: Bayesian clustering analyses for genetic assignment and study of hybridization in oaks: effects of asymmetric phylogenies and asymmetric sampling schemes
Bayesian clustering methods have been widely used for studying species delimitation and genetic introgression. In order to test the effect of phylogenetic relationships and sampling scheme on the inferred clustering solution and on the performance of Bayesian clustering analysis, I simulated genotypes of the interfertile oak species Quercus robur, Quercus petraea, and Quercus pubescens and I run analyses using two popular software programs, STRUCTURE and BAPS. First, based on purebred simulations, I compared clustering solutions resulting from different sample size configurations. While clustering solution generally reflected the taxonomic relationships when equal samples of each species were included, spurious partition was inferred by STRUCTURE when some species were represented by larger and others by smaller samples. In very unbalanced configurations, STRUCTURE failed to identify the three species, even if three subpopulations were assumed. By contrast, BAPS could properly identify the three species under any sampling scheme. Second, based on simulations of purebreds and hybrids, I tested the performance of individual assignments with variable number of loci. This analysis showed that STRUCTURE can detect introgressed individuals more efficiently than BAPS. However, BAPS could assign purebreds more efficiently with a lower number of loci. Method performance also depended on phylogenetic relationships. In the case of Q. petraea, Q. pubescens, and their hybrids, method performance was lower due to their phylogenetic affinity. Inclusion of three instead of two species into the analysis led to reduction of performance, and to misclassification of hybrids, which often reflected the phylogenetic affinity between Q. petraea and Q. pubescens.
Data from: Genotyping-by-sequencing for Populus population genomics: an assessment of genome sampling patterns and filtering approaches
Continuing advances in nucleotide sequencing technology are inspiring a suite of genomic approaches in studies of natural populations. Researchers are faced with data management and analytical scales that are increasing by orders of magnitude. With such dramatic advances comes a need to understand biases and error rates, which can be propagated and magnified in large-scale data acquisition and processing. Here we assess genomic sampling biases and the effects of various population-level data filtering strategies in a genotyping-by-sequencing (GBS) protocol. We focus on data from two species of Populus, because this genus has a relatively small genome and is emerging as a target for population genomic studies. We estimate the proportions and patterns of genomic sampling by examining the Populus trichocarpa genome (Nisqually-1), and demonstrate a pronounced bias towards coding regions when using the methylation-sensitive ApeKI restriction enzyme in this species. Using population-level data from a closely related species (P. tremuloides), we also investigate various approaches for filtering GBS data to retain high-depth, informative SNPs that can be used for population genetic analyses. We find a data filter that includes the designation of ambiguous alleles resulted in metrics of population structure and Hardy-Weinberg equilibrium that were most consistent with previous studies of the same populations based on other genetic markers. Analyses of the filtered data (27,910 SNPs) also resulted in patterns of heterozygosity and population structure similar to a previous study using microsatellites. Our application demonstrates that technically and analytically simple approaches can readily be developed for population genomics of natural populations.
Data from: Phylogenetic systematics of subtribe Spiranthinae (Orchidaceae: Orchidoideae: Cranichideae) based on nuclear and plastid DNA sequences of a nearly complete generic sample
Subtribe Spiranthinae is the most species-rich lineage of terrestrial Neotropical orchids, encompassing > 500 species and 40 genera. We conducted maximum parsimony and maximum likelihood phylogenetic analyses of DNA sequence data of plastid matK-trnK and trnL-trnF and nuclear ribosomal ITS sequences for 36 genera and 182 species of Spiranthinae plus appropriate outgroups. The results strongly support monophyly of Spiranthinae (minus Discyphus, Discyphinae and Galeottiella, Galeottiellinae) and five major lineages, namely monospecific Cotylolabium (sister to the remaining Spiranthinae) and the Eurystyles, Pelexia, Spiranthes and Stenorrhynchos clades. Eighteen of the 27 genera of Spiranthinae for which more than one species was included in our analyses are monophyletic. Paraphyly of large genera, such as Cyclopogon and Sarcoglottis, resulted from segregation of particular species or groups of species exhibiting minor modifications of structures directly involved in pollination (e.g. nectary, rostellum and viscidium). Conversely, polyphyly has resulted from convergent evolution of floral attributes in distantly related species (e.g. Mesadenus). Some of the morphological characters used traditionally for generic delimitation and in non-molecular cladistic analyses of Spiranthinae are discussed against the evolutionary framework set by our molecular trees, emphasizing putative synapomorphies and problems derived from inappropriate character coding or incorrect homology assessments. Our ancestral area analysis indicates that Spiranthinae originated in eastern South America, with subsequent migrations and secondary radiations in Mesoamerica and North America, plus a derived migration from the latter region to the Old World (Spiranthes).
Data from: Subsampling reveals that unbalanced sampling affects STRUCTURE results in a multi-species dataset
Studying the genetic population structure of species can reveal important insights into several key evolutionary, historical, demographic, and anthropogenic processes. One of the most important statistical tools for inferring genetic clusters is the program STRUCTURE. Recently, several papers have pointed out that STRUCTURE may show a bias when the sampling design is unbalanced, resulting in spurious joining of underrepresented populations and spurious separation of overrepresented populations. Suggestions to overcome this bias include subsampling and changing the ancestry model, but the performance of these two methods has not yet been tested on actual data. Here, I use a dataset of twelve high-alpine plant species to test whether unbalanced sampling affects the STRUCTURE inference of population differentiation between the European Alps and the Carpathians. For four of the twelve species, subsampling of the Alpine populations –to match the sample size between the Alps and the Carpathians– resulted in a drastically different clustering than the full dataset. On the other hand, STRUCTURE results with the alternative ancestry model were indistinguishable from the results with the default model. Based on these results, the subsampling strategy seems a more viable approach to overcome the bias than the alternative ancestry model. However, subsampling is only possible when there is an a priori expectation of what constitute the main clusters. Though these results do not mean that the use of STRUCTURE should be discarded, it does indicate that users of the software should be cautious about the interpretation of the results when sampling is unbalanced.
Data from: Effects of growth rate, size, and light availability on tree survival across life stages: a demographic analysis accounting for missing values and small sample sizes
Background: Plant survival is a key factor in forest dynamics and survival probabilities often vary across life stages. Studies specifically aimed at assessing tree survival are unusual and so data initially designed for other purposes often need to be used; such data are more likely to contain errors than data collected for this specific purpose. Results: We investigate the survival rates of ten tree species in a dataset designed to monitor growth rates. As some individuals were not included in the census at some time points we use capture-mark-recapture methods both to allow us to account for missing individuals, and to estimate relocation probabilities. Growth rates, size, and light availability were included as covariates in the model predicting survival rates. The study demonstrates that tree mortality is best described as constant between years and size-dependent at early life stages and size independent at later life stages for most species of UK hardwood. We have demonstrated that even with a twenty-year dataset it is possible to discern variability both between individuals and between species. Conclusions: Our work illustrates the potential utility of the method applied here for calculating plant population dynamics parameters in time replicated datasets with small sample sizes and missing individuals without any loss of sample size, and including explanatory covariates.
Data from: Evolutionary and dispersal history of Eurasian wild mice Mus musculus clarified by more extensive geographic sampling of mitochondrial DNA
We examined sequence variation of mitochondrial DNA control region and cytochrome b gene of the house mouse (Mus musculus sensu lato) drawn from ca. 200 localities, with 290 new samples drawn primarily from previously unsampled portions of their Eurasian distribution and with the objective of further clarifying evolutionary episodes of this species before and after the onset of human-mediated long-distance dispersals. Phylogenetic analysis of the expanded data detected five equally distinct clades, with geographic ranges of northern Eurasia (musculus, MUS), India and Southeast Asia (castaneus, CAS), Nepal (unspecified), western Europe (domesticus, DOM), and Yemen (gentilulus). Our results confirm previous suggestions of Southwestern Asia as the likely place of origin of M. musculus and the region of Iran, Afghanistan, Pakistan, and northern India, specifically as the ancestral homeland of CAS. The divergence of the subspecies lineages and of internal sublineage differentiation within CAS were estimated to be 0.37-0.47 and 0.14-0.23 million years ago (mya), respectively, assuming a split of M. musculus and Mus spretus at 1.7 mya. Of four CAS sublineages detected, only one extends to eastern parts of India, Southeast Asia, Indonesia, Philippines, South China, Northeast China, Primorye, Sakhalin and Japan, implying a dramatic range expansion of CAS out of its homeland during an evolutionary short time, perhaps associated with the spread of agricultural practices. Multiple and non-coincident eastward dispersal events of MUS sublineages to distant geographic areas, such as northern China, Russia, and Korea, are inferred, with the possibility of several different routes.
Data from: An optimized protocol for large-scale in situ sampling and analysis of volatile organic compounds
Chemical ecology is an ever‐expanding field with a growing interest in population‐ and community‐level studies. Many such studies are hindered due to lack of an efficient and accelerated protocol for large‐scale sampling and analysis of chemical compounds. Here, we present an optimized protocol for such large‐scale study of volatiles. A large‐scale in situ study to understand role of semiochemicals in variation in mating success of lekking blackbuck was conducted. Suitable methods for sampling and statistical analysis were identified by testing and comparing the efficiencies of available techniques to reduce analysis time while retaining sensitivity and comprehensiveness. Solid‐phase extraction using polydimethylsiloxane, analysis using a semiautomated detection of retention time and base peak, and statistical analysis using random forest algorithm were identified as the most efficient methods for large‐scale in situ sampling and analysis of volatiles. The protocol for large‐scale volatile analysis can facilitate evolutionary and metaecological studies of volatiles in situ from all types of biological samples. The protocol has potential for wider application with the analysis and interpretation methods being suitable for all kinds of semiochemicals, including nonvolatile chemicals.
Data from: Empowering conservation practice with efficient and economical genotyping from poor quality samples
1. Moderate to high density genotyping (100+ SNPs) is widely used to determine and measure individual identity, relatedness, fitness, population structure and migration in wild populations. 2. However, these important tools are difficult to apply when high-quality genetic material is unavailable. Most genomic tools are developed for high quality DNA sources from lab or medical settings. As a result, most genetic data from market or field settings is limited to easily-amplified mitochondrial DNA or a few microsatellites. 3. To enable genotyping in conservation contexts, we used next-generation sequencing of multiplex PCR products from very low-quality DNA extracted from feces, hair, and cooked samples. We demonstrated utility and wide-ranging potential application in endangered wild tigers and tracking commercial trade in Caribbean queen conch. 4. We genotyped 100 SNPs from degraded tiger samples to identify individuals, discern close relatives, and detect population differentiation. Co-occurring carnivores do not amplify (e.g. Indian wild dog/Dhole) or are monomorphic (e.g. leopard). 62 SNPs from conch fritters and field-collected samples were used to test relatedness and detect population structure. 5. We provide proof-of-concept for a rapid, simple, cost-effective, and scalable method (for both samples and number of loci), a framework that can be applied to other conservation scenarios previously limited by low quality DNA samples. These approaches provide a critical advance for wildlife monitoring and forensics, open the door to field-ready testing, and will strengthen the use of science in policy decisions and wildlife trade.
Data from: Out-of-sample predictions from plant–insect food webs: robustness to missing and erroneous trophic interaction records
With increasing biotic introductions, there is a great need for predictive tools to anticipate which new trophic interactions will develop and which will not. Phylogenetic constraint of interactions in both native and novel food webs can make some novel interactions predictable. However, many food webs are sparsely sampled, or may include inaccurate interactions. In such cases, it is unclear whether modeling methods are still useful to anticipate novel interactions. We ran bootstrap simulations of host-use models on a Lepidoptera–plant data set to remove native trophic records or add erroneous records in order to observe the effect of missing or erroneous data on the prediction of interactions with novel plants. We found that the model was robust to a large amount of missing interaction records, but lost predictive power with the addition of relatively few erroneous interaction records. The loss of predictive power with missing records was due to inaccuracy in estimating phylogenetic distance between native and novel hosts. Removal of interaction records proportionally to their encounter frequency in the field had little effect on the loss of predictive power. Host-use models may have immediate value for predicting novel interactions from large, but sparsely sampled databases of trophic interactions.
Data from: A genetic demographic analysis of Lake Malawi rock-dwelling cichlids using spatio-temporal sampling
We estimated the effective population sizes (Ne) and tested for short-term temporal demographic stability of populations of two Lake Malawi cichlids: Maylandia benetos, a micro-endemic, and Maylandia zebra, a widespread species found across the lake. We sampled a total of 351 individuals, genotyped them at 13 microsatellite loci and sequenced their mitochondrial D-loop to estimate genetic diversity, population structure, demographic history and effective population sizes. At the microsatellite loci, genetic diversity was high in all populations. Yet, genetic diversity was relatively low for the sequence data. Microsatellites yielded mean Ne estimates of 481 individuals (±99 SD) for M. benetos and between 597 (±106.3 SD) and 1524 (±483.9 SD) individuals for local populations of M. zebra. The microsatellite data indicated no deviations from mutation–drift equilibrium. Maylandia zebra was further found to be in migration–drift equilibrium. Temporal fluctuations in allele frequencies were limited across the sampling period for both species. Bayesian Skyline analyses suggested a recent expansion of M. zebra populations in line with lake-level fluctuations, whereas the demographic history of M. benetos could only be estimated for the very recent past. Divergence time estimates placed the origin of M. benetos within the last 100 ka after the refilling of the lake and suggested that it split off the sympatric M. zebra population. Overall, our data indicate that micro-endemics and populations in less favourable habitats have smaller Ne, indicating that drift may play an important role driving their divergence. Yet, despite small population sizes, high genetic variation can be maintained.
Data from: Informative plot sizes in presence-absence sampling of forest floor vegetation
1. Plant communities are attracting increased interest in connection with forest and landscape inventories due to society's interest in ecosystem services. However, the acquisition of accurate information about plant communities poses several methodological challenges. Here we investigate the use of presence-absence sampling with the aim to monitor state and change of plant density. We study what plot sizes are informative, i.e. the estimators should have as high precision as possible. 2. Plant occurrences were modeled through different Poisson processes and tests were developed for assessing the plausibility of the model assumptions. Optimum plot sizes were determined by minimizing the variance of the estimators. While state estimators of similar kind as ours have been proposed in previous studies, our tests and change estimation procedures are new. 3. We found that the most informative plot size for state estimation is 1.6 divided by the plant density, i.e. if the true density is 1 plant per square meter the optimum plot size is 1.6 square meters. This is in accordance with previous findings. More importantly, the most informative plot size for change estimation was smaller and depended on the change patterns. We provide theoretical results as well as some empirical results based on data from the Swedish National Forest Inventory. 4. Use of too small or too large plots resulted in poor precision of the density (and density change) estimators. As a consequence, a range of different plot sizes would be required for jointly monitoring both common and rare plants using presence-absence sampling in monitoring programmes.
Data from: Heritability estimates from genome wide relatedness matrices in wild populations: application to a passerine, using a small sample size
Genomic developments have empowered the investigation of heritability in wild populations directly from genome wide relatedness matrices (GRM). Such GRM based approaches can in particular be used to improve or substitute approaches based on social pedigree (PED-social). However, measuring heritability from GRM in the wild has not been widely applied yet, especially using small samples and in non-model species. Here, we estimated heritability for four quantitative traits (tarsus length, wing length, bill length and body mass), using PED-social and a pedigree corrected by genetic data (PED-corrected) and GRM from a small sample (n = 494) of blue tits from natural populations in Corsica genotyped at nearly 50,000 filtered SNPs derived from RAD-seq. We also measured genetic correlations among traits and we performed chromosome partitioning. Heritability estimates were slightly higher when using GRM compared to PED-social, and PED-corrected yielded intermediate values, suggesting a minor underestimation of heritability in PED-social due to incorrect pedigree links, including extra-pair paternity, and to lower information content than the GRM. Genetic correlations among traits were similar between PED-social and GRM but credible intervals were very large in both cases, suggesting a lack of power for this small dataset. Although a positive linear relationship was found between the number of genes per chromosomes and the chromosome heritability for tarsus length, chromosome partitioning similarly showed a lack of power for the three other traits. We discuss the usefulness and limitations of the quantitative genetic inferences based on genomic data in small samples from wild populations.
Data from: Fully-sampled phylogenies of squamates reveal evolutionary patterns in threat status
Macroevolutionary rates of diversification and anthropogenic extinction risk differ vastly throughout the Tree of Life. This results in a highly heterogeneous distribution of Evolutionary distinctiveness (ED) and threat status among species. We examine the phylogenetic distribution of ED and threat status for squamates (amphisbaenians, lizards, and snakes) using fully-sampled phylogenies containing 9574 species and expert-based estimates of threat status for ~ 4000 species. We ask whether threatened species are more closely related than would be expected by chance and whether high-risk species represent a disproportionate amount of total evolutionary history. We found currently-assessed threat status to be phylogenetically clustered at broad level in Squamata, suggesting it is critical to assess extinction risks for close relatives of threatened lineages. Our findings show no association between threat status and ED, suggesting that future extinctions may not result in a disproportionate loss of evolutionary history. Lizards in degraded tropical regions (e.g., Madagascar, India, Australia, and the West Indies) seem to be at particular risk. A low number of threatened high-ED species in areas like the Amazon, Borneo, and Papua New Guinea may be due to a dearth of adequate risk assessments. It seems we have not yet reached a tipping point of extinction risk affecting a majority of species; 63% of the assessed species are not threatened and 56% are Least Concern. Nonetheless, our results show that immediate efforts should focus on geckos, iguanas, and chameleons, representing 67% of high-ED threatened species and 57% of Unassessed high-ED lineages.
Data from: SNP genotyping identifies new signatures of selection in a deep sample of West African P. falciparum malaria parasites
We used a high density SNP array to genotype 75 P. falciparum isolates recently collected from Senegal and The Gambia in order to search for signals of selection in this malaria endemic region. We found little geographic or temporal stratification of the genetic diversity among the sampled parasites. Through application of the iHS and REHH haplotype-based tests for positive selection, we found evidence of recent selective sweeps at a known drug resistance locus, at several known antigenic loci, and at several genomic regions not previously identified as sites of recent selection. We discuss the value of deep population-specific genomic analyses for identifying selection signals within sampled endemic populations of parasites, which may correspond to local selection pressures such as distinctive therapeutic regimes or mosquito vectors.
Data from: Relationship type affects the reliability of dispersal distance estimated using pedigree inferences in partially sampled populations: a case study involving invasive American mink in Scotland
Estimating dispersal—a key parameter for population ecology and management—is notoriously difficult. The use of pedigree assignments, aided by likelihood-based software, has become popular to estimate dispersal rate and distance. However, the partial sampling of populations may produce false assignments. Further, it is unknown how the accuracy of assignment is affected by the genealogical relationships of individuals and is reflected by software-derived assignment probabilities. Inspired by a project managing invasive American mink (Neovison vison), we estimated individual dispersal distances using inferred pairwise relationships of culled individuals. Additionally, we simulated scenarios to investigate the accuracy of pairwise inferences. Estimates of dispersal distance varied greatly when derived from different inferred pairwise relationships, with mother–offspring relationship being the shortest (average = 21 km) and the most accurate. Pairs assigned as maternal half-siblings were inaccurate, with 64%–97% falsely assigned, implying that estimates for these relationships in the wild population were unreliable. The false assignment rate was unrelated to the software-derived assignment probabilities at high dispersal rates. Assignments were more accurate when the inferred parents were older and immigrants and when dispersal rates between subpopulations were low (1% and 2%). Using 30 instead of 15 loci increased pairwise reliability, but half-sibling assignments were still inaccurate (>59% falsely assigned). The most reliable approach when using inferred pairwise relationships in polygamous species would be not to use half-sibling relationship types. Our simulation approach provides guidance for the application of pedigree inferences under partial sampling and is applicable to other systems where pedigree assignments are used for ecological inference.
Data from: Parallel tagged next-generation sequencing on pooled samples – a new approach for population genetics in ecology and conservation
Next-generation sequencing (NGS) on pooled samples has already been broadly applied in human medical diagnostics and plant and animal breeding. However, thus far it has been only sparingly employed in ecology and conservation, where it may serve as a useful diagnostic tool for rapid assessment of species genetic diversity and structure at the population level. Here we undertake a comprehensive evaluation of the accuracy, practicality and limitations of parallel tagged amplicon NGS on pooled population samples for estimating species population diversity and structure. We obtained 16S and Cyt b data from 20 populations of Leiopelma hochstetteri, a frog species of conservation concern in New Zealand, using two approaches – parallel tagged NGS on pooled population samples and individual Sanger sequenced samples. Data from each approach were then used to estimate two standard population genetic parameters, nucleotide diversity (π) and population differentiation (FST), that enable population genetic inference in a species conservation context. We found a positive correlation between our two approaches for population genetic estimates, showing that the pooled population NGS approach is a reliable, rapid and appropriate method for population genetic inference in an ecological and conservation context. Our experimental design also allowed us to identify both the strengths and weaknesses of the pooled population NGS approach and outline some guidelines and suggestions that might be considered when planning future projects.
Data from: Optimising sampling of flying insects using a modified window trap
Insect populations are globally declining but standardized long‐term data to evaluate trends and consequences are largely missing. One difficulty among many is the rather narrow taxonomic cover of most conventional trap types, which makes the use of several complementary collection methods necessary to achieve comprehensive coverage. To avoid the effort associated with operating multiple traps, we demonstrate how to modify window traps in a simple and standardizable way to capture a wider range of flying insect taxa. While a typical window trap only has a collection unit below the windows, we added an additional collection unit on top of the windows. We tested this modified trap design in 135 study plots in a temperate forest over 5 months and compared trap catches between top and bottom collection units. The top collection unit captured considerably more individuals of Hymenoptera, Diptera, Lepidoptera, Neuroptera, Auchenorrhyncha and Thysanoptera than the bottom collection unit. In contrast, there were more individuals of Coleoptera, Heteroptera, Sternorrhyncha and Psocoptera in the bottom collection unit. Both collection units captured a highly distinct insect community and patterns were consistent throughout the season. These modified traps are suitable for collecting a broader range of flying insects compared to conventional window traps. The additional top unit is fast and easy to build and the traps require little maintenance while operating in the field. These characteristics make modified window traps with top and bottom collection units a promising tool for standardized and replicable biodiversity studies covering a broad range of insect taxa.
Data from: Molecular ecology of the Neotropical otter (Lontra longicaudis): non-invasive sampling yields insights into local population dynamics
Non-invasive genetic analysis has been frequently employed to estimate ecological and population parameters for many secretive and/or threatened species. However, Neotropical carnivores have so far been scarcely targeted by such studies. The Neotropical otter (Lontra longicaudis) is a poorly-known species for which local levels of genetic diversity and demographic parameters are virtually absent. We employed non-invasive sampling and amplification of microsatellite loci to investigate population size and density, spatial organization, and relatedness of a wild Neotropical otter population in an Atlantic forest area in southern Brazil. We directly identified 28 individuals and estimate a rather high population density at the study site. Spatial organization analysis indicated that male cumulative displacement was higher than that of females, with the latter sex showing evidence of philopatric behaviour. Also, the reconstruction of genealogical relationships suggests that spatial organization in this otter appears to be influenced by relatedness. By allowing the testing of specific hypothesis targeting these issues, our results provided important glimpses into the Neotropical otter's population biology. Moreover, the findings of the present study reaffirm the power of non-invasive genetics to investigate the biology of this elusive species, and open up new avenues for ecological and demographic studies of other Neotropical carnivores.
RNAseq data for Red-Face Hereford Carcass Quality Pooled Samples
<p>Fold change and FPKM data from RNAseq of Muscle tissue samples from Red-Faced Herefords of differing carcass quality collected at harvest.</p>
Data from: Hierarchical distance sampling to estimate population sizes of common lizards across a desert ecoregion
1) Multi-species wildlife monitoring across large geographical regions is important for effective conservation planning in response to expected impacts from climate change and land use. Unlike many species of birds, mammals, and amphibians which can be efficiently sampled using automated sensors including cameras and sound recorders, reptiles are often much more challenging to detect, in part because of their typically cryptic behavior and generally small body sizes. Although many lizard species are more active during the day which makes them easier to detect using visual encounter surveys, they may be unavailable for sampling during certain periods of the day or year due to their sensitivity to temperature. 2) In recognition of these sampling challenges, we demonstrate application of a recent innovation in distance sampling that adjusts for temporary emigration between repeat survey visits. We used transect surveys to survey lizards at 229 sites throughout the Mojave Desert in California, USA, 2016. 3) We estimated a total population size of 80 million (90% CI: 64–97 million) for the three most common species of lizards across this 66,830 km2 ecoregion. We mapped how density at the 1-km2 scale was predicted to vary with vegetation cover and human development. We validated these results against independent surveys from the southern portion of our study area. 4) Our methods and results demonstrate how multi-species monitoring programs spanning arid ecoregions can better incorporate information about reptiles.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.